Describe when TF-IDF is a useful baseline for text classification or search.
Reframe: TF-IDF gives you a cheap, explainable floor. The Concept A bag-of-words model turns documents into counts. TF-IDF improves that count by asking whether a term is frequent in this document but not common everywhere. That is why a rare, label-specific term can matter more than a common support phrase. Why It Works Many workplace text problems have visible lexical signals: refund, password, invoice, outage, escalation. TF-IDF captures those signals without pretending to understand grammar or intent. It is fast to train, easy to inspect, and strong enough to expose which labels are vocabulary-driven. Where It Breaks TF-IDF does not…
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